Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations8250
Missing cells7667
Missing cells (%)7.7%
Duplicate rows85
Duplicate rows (%)1.0%
Total size in memory773.6 KiB
Average record size in memory96.0 B

Variable types

Numeric10
DateTime2

Alerts

Dataset has 85 (1.0%) duplicate rowsDuplicates
OVD_sum is highly overall correlated with OVD_t1 and 2 other fieldsHigh correlation
OVD_t1 is highly overall correlated with OVD_sum and 1 other fieldsHigh correlation
OVD_t2 is highly overall correlated with OVD_sum and 2 other fieldsHigh correlation
OVD_t3 is highly overall correlated with OVD_sum and 1 other fieldsHigh correlation
prod_limit has 6118 (74.2%) missing values Missing
highest_balance has 409 (5.0%) missing values Missing
report_date has 1114 (13.5%) missing values Missing
new_balance is highly skewed (γ1 = 79.0773819) Skewed
highest_balance is highly skewed (γ1 = 47.71863449) Skewed
OVD_t1 has 7475 (90.6%) zeros Zeros
OVD_t2 has 7886 (95.6%) zeros Zeros
OVD_t3 has 7983 (96.8%) zeros Zeros
OVD_sum has 7330 (88.8%) zeros Zeros
pay_normal has 285 (3.5%) zeros Zeros
prod_code has 147 (1.8%) zeros Zeros
new_balance has 3864 (46.8%) zeros Zeros

Reproduction

Analysis started2025-03-12 01:56:39.346941
Analysis finished2025-03-12 01:56:45.785809
Duration6.44 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

Distinct1125
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57821730
Minimum54982353
Maximum59006239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:45.834789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum54982353
5-th percentile54984182
Q154990497
median58989048
Q358996551
95-th percentile59003954
Maximum59006239
Range4023886
Interquartile range (IQR)4006054

Descriptive statistics

Standard deviation1822724
Coefficient of variation (CV)0.031523165
Kurtosis-1.1676063
Mean57821730
Median Absolute Deviation (MAD)9099
Skewness-0.91248548
Sum4.7702928 × 1011
Variance3.3223226 × 1012
MonotonicityNot monotonic
2025-03-11T22:56:45.915949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58988212 55
 
0.7%
54990497 48
 
0.6%
58998646 45
 
0.5%
58991343 39
 
0.5%
58987276 39
 
0.5%
54989251 37
 
0.4%
59000307 33
 
0.4%
58999208 32
 
0.4%
54991742 32
 
0.4%
59000510 31
 
0.4%
Other values (1115) 7859
95.3%
ValueCountFrequency (%)
54982353 18
0.2%
54982356 7
 
0.1%
54982387 11
0.1%
54982463 2
 
< 0.1%
54982530 4
 
< 0.1%
54982549 10
0.1%
54982579 22
0.3%
54982665 4
 
< 0.1%
54982697 2
 
< 0.1%
54982721 10
0.1%
ValueCountFrequency (%)
59006239 3
 
< 0.1%
59006219 3
 
< 0.1%
59006193 8
0.1%
59006139 4
< 0.1%
59005995 3
 
< 0.1%
59005917 2
 
< 0.1%
59005881 3
 
< 0.1%
59005880 8
0.1%
59005871 5
0.1%
59005860 6
0.1%

OVD_t1
Real number (ℝ)

High correlation  Zeros 

Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24909091
Minimum0
Maximum34
Zeros7475
Zeros (%)90.6%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:45.977731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum34
Range34
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2501966
Coefficient of variation (CV)5.0190376
Kurtosis203.50205
Mean0.24909091
Median Absolute Deviation (MAD)0
Skewness11.350079
Sum2055
Variance1.5629917
MonotonicityNot monotonic
2025-03-11T22:56:46.029650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 7475
90.6%
1 397
 
4.8%
2 147
 
1.8%
3 61
 
0.7%
4 61
 
0.7%
5 26
 
0.3%
6 20
 
0.2%
7 15
 
0.2%
8 14
 
0.2%
9 9
 
0.1%
Other values (11) 25
 
0.3%
ValueCountFrequency (%)
0 7475
90.6%
1 397
 
4.8%
2 147
 
1.8%
3 61
 
0.7%
4 61
 
0.7%
5 26
 
0.3%
6 20
 
0.2%
7 15
 
0.2%
8 14
 
0.2%
9 9
 
0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
31 2
 
< 0.1%
23 1
 
< 0.1%
17 1
 
< 0.1%
16 2
 
< 0.1%
15 2
 
< 0.1%
14 3
< 0.1%
13 2
 
< 0.1%
12 4
< 0.1%
11 5
0.1%

OVD_t2
Real number (ℝ)

High correlation  Zeros 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.12715152
Minimum0
Maximum34
Zeros7886
Zeros (%)95.6%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.155874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum34
Range34
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.86004635
Coefficient of variation (CV)6.7639489
Kurtosis406.08777
Mean0.12715152
Median Absolute Deviation (MAD)0
Skewness15.318031
Sum1049
Variance0.73967973
MonotonicityNot monotonic
2025-03-11T22:56:46.204863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 7886
95.6%
2 127
 
1.5%
1 111
 
1.3%
3 43
 
0.5%
4 31
 
0.4%
5 12
 
0.1%
6 9
 
0.1%
7 9
 
0.1%
9 7
 
0.1%
10 4
 
< 0.1%
Other values (6) 11
 
0.1%
ValueCountFrequency (%)
0 7886
95.6%
1 111
 
1.3%
2 127
 
1.5%
3 43
 
0.5%
4 31
 
0.4%
5 12
 
0.1%
6 9
 
0.1%
7 9
 
0.1%
8 3
 
< 0.1%
9 7
 
0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
23 1
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
11 4
< 0.1%
10 4
< 0.1%
9 7
0.1%
8 3
 
< 0.1%
7 9
0.1%
6 9
0.1%

OVD_t3
Real number (ℝ)

High correlation  Zeros 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.36921212
Minimum0
Maximum35
Zeros7983
Zeros (%)96.8%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.258432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.9003196
Coefficient of variation (CV)7.8554289
Kurtosis99.087751
Mean0.36921212
Median Absolute Deviation (MAD)0
Skewness9.6446005
Sum3046
Variance8.4118535
MonotonicityNot monotonic
2025-03-11T22:56:46.318394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 7983
96.8%
1 46
 
0.6%
2 35
 
0.4%
3 22
 
0.3%
35 15
 
0.2%
6 14
 
0.2%
5 13
 
0.2%
34 12
 
0.1%
4 12
 
0.1%
9 12
 
0.1%
Other values (23) 86
 
1.0%
ValueCountFrequency (%)
0 7983
96.8%
1 46
 
0.6%
2 35
 
0.4%
3 22
 
0.3%
4 12
 
0.1%
5 13
 
0.2%
6 14
 
0.2%
7 5
 
0.1%
8 4
 
< 0.1%
9 12
 
0.1%
ValueCountFrequency (%)
35 15
0.2%
34 12
0.1%
33 6
 
0.1%
32 4
 
< 0.1%
31 3
 
< 0.1%
30 2
 
< 0.1%
26 1
 
< 0.1%
25 2
 
< 0.1%
24 5
 
0.1%
23 3
 
< 0.1%

OVD_sum
Real number (ℝ)

High correlation  Zeros 

Distinct393
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.6817
Minimum0
Maximum31500
Zeros7330
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.383680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile107.55
Maximum31500
Range31500
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1804.2326
Coefficient of variation (CV)9.613258
Kurtosis185.91802
Mean187.6817
Median Absolute Deviation (MAD)0
Skewness13.091835
Sum1548374
Variance3255255.2
MonotonicityNot monotonic
2025-03-11T22:56:46.453161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7330
88.8%
1 76
 
0.9%
30 52
 
0.6%
15 19
 
0.2%
6 15
 
0.2%
2 15
 
0.2%
25 13
 
0.2%
45 12
 
0.1%
16 12
 
0.1%
60 11
 
0.1%
Other values (383) 695
 
8.4%
ValueCountFrequency (%)
0 7330
88.8%
1 76
 
0.9%
2 15
 
0.2%
3 8
 
0.1%
4 6
 
0.1%
5 7
 
0.1%
6 15
 
0.2%
7 10
 
0.1%
8 1
 
< 0.1%
9 7
 
0.1%
ValueCountFrequency (%)
31500 2
< 0.1%
31300 1
< 0.1%
30600 2
< 0.1%
30312 1
< 0.1%
29922 1
< 0.1%
29890 1
< 0.1%
29700 1
< 0.1%
29645 1
< 0.1%
28984 1
< 0.1%
28105 1
< 0.1%

pay_normal
Real number (ℝ)

Zeros 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.526667
Minimum0
Maximum36
Zeros285
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.516097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median11
Q325
95-th percentile36
Maximum36
Range36
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.053627
Coefficient of variation (CV)0.82975865
Kurtosis-1.0761803
Mean14.526667
Median Absolute Deviation (MAD)9
Skewness0.55839522
Sum119845
Variance145.28993
MonotonicityNot monotonic
2025-03-11T22:56:46.578861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 910
 
11.0%
36 651
 
7.9%
2 419
 
5.1%
3 345
 
4.2%
4 315
 
3.8%
9 299
 
3.6%
6 294
 
3.6%
35 286
 
3.5%
0 285
 
3.5%
10 284
 
3.4%
Other values (27) 4162
50.4%
ValueCountFrequency (%)
0 285
 
3.5%
1 910
11.0%
2 419
5.1%
3 345
 
4.2%
4 315
 
3.8%
5 283
 
3.4%
6 294
 
3.6%
7 279
 
3.4%
8 283
 
3.4%
9 299
 
3.6%
ValueCountFrequency (%)
36 651
7.9%
35 286
3.5%
34 168
 
2.0%
33 119
 
1.4%
32 105
 
1.3%
31 117
 
1.4%
30 86
 
1.0%
29 88
 
1.1%
28 121
 
1.5%
27 103
 
1.2%

prod_code
Real number (ℝ)

Zeros 

Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.232
Minimum0
Maximum27
Zeros147
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.635063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median10
Q310
95-th percentile13
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.5330549
Coefficient of variation (CV)0.42918548
Kurtosis2.4727832
Mean8.232
Median Absolute Deviation (MAD)0
Skewness0.036071404
Sum67914
Variance12.482477
MonotonicityNot monotonic
2025-03-11T22:56:46.686121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
10 4523
54.8%
6 1144
 
13.9%
5 962
 
11.7%
1 427
 
5.2%
13 425
 
5.2%
2 239
 
2.9%
0 147
 
1.8%
7 147
 
1.8%
12 56
 
0.7%
19 35
 
0.4%
Other values (11) 145
 
1.8%
ValueCountFrequency (%)
0 147
 
1.8%
1 427
 
5.2%
2 239
 
2.9%
3 21
 
0.3%
4 4
 
< 0.1%
5 962
11.7%
6 1144
13.9%
7 147
 
1.8%
8 24
 
0.3%
9 3
 
< 0.1%
ValueCountFrequency (%)
27 3
 
< 0.1%
26 14
 
0.2%
25 5
 
0.1%
24 24
 
0.3%
22 3
 
< 0.1%
19 35
 
0.4%
17 22
 
0.3%
15 22
 
0.3%
13 425
5.2%
12 56
 
0.7%

prod_limit
Real number (ℝ)

Missing 

Distinct321
Distinct (%)15.1%
Missing6118
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean85789.702
Minimum1.1
Maximum660000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:46.746388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.1
5-th percentile11000
Q137400
median68200
Q3112200
95-th percentile215847.5
Maximum660000
Range659998.9
Interquartile range (IQR)74800

Descriptive statistics

Standard deviation74345.828
Coefficient of variation (CV)0.8666055
Kurtosis11.844532
Mean85789.702
Median Absolute Deviation (MAD)36300
Skewness2.6682966
Sum1.8290365 × 108
Variance5.5273022 × 109
MonotonicityNot monotonic
2025-03-11T22:56:46.818459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55000 103
 
1.2%
11000 86
 
1.0%
33000 51
 
0.6%
27500 47
 
0.6%
22000 46
 
0.6%
82500 45
 
0.5%
44000 44
 
0.5%
16500 37
 
0.4%
110000 37
 
0.4%
66000 35
 
0.4%
Other values (311) 1601
 
19.4%
(Missing) 6118
74.2%
ValueCountFrequency (%)
1.1 1
 
< 0.1%
1100 2
 
< 0.1%
1650 3
< 0.1%
2090 2
 
< 0.1%
2200 5
0.1%
2750 3
< 0.1%
4070 1
 
< 0.1%
5500 6
0.1%
6050 1
 
< 0.1%
9240 1
 
< 0.1%
ValueCountFrequency (%)
660000 3
< 0.1%
566500 1
 
< 0.1%
550000 4
< 0.1%
543400 1
 
< 0.1%
526900 1
 
< 0.1%
481800 1
 
< 0.1%
468600 1
 
< 0.1%
458700 1
 
< 0.1%
412500 3
< 0.1%
410300 1
 
< 0.1%
Distinct3041
Distinct (%)37.0%
Missing26
Missing (%)0.3%
Memory size64.6 KiB
Minimum1988-07-19 00:00:00
Maximum2016-05-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-11T22:56:46.907523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:46.979605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

new_balance
Real number (ℝ)

Skewed  Zeros 

Distinct3939
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105404.2
Minimum-40303.2
Maximum1.6321196 × 108
Zeros3864
Zeros (%)46.8%
Negative372
Negative (%)4.5%
Memory size64.6 KiB
2025-03-11T22:56:47.047327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-40303.2
5-th percentile0
Q10
median0
Q324948
95-th percentile313394.64
Maximum1.6321196 × 108
Range1.6325226 × 108
Interquartile range (IQR)24948

Descriptive statistics

Standard deviation1887704.1
Coefficient of variation (CV)17.909193
Kurtosis6770.8746
Mean105404.2
Median Absolute Deviation (MAD)76.2
Skewness79.077382
Sum8.6958464 × 108
Variance3.5634269 × 1012
MonotonicityNot monotonic
2025-03-11T22:56:47.119317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3864
46.8%
-1.2 81
 
1.0%
-2.4 16
 
0.2%
-4.8 12
 
0.1%
-3.6 10
 
0.1%
1.2 7
 
0.1%
682.8 6
 
0.1%
673.2 6
 
0.1%
18000 6
 
0.1%
6000 6
 
0.1%
Other values (3929) 4236
51.3%
ValueCountFrequency (%)
-40303.2 1
< 0.1%
-32662.8 1
< 0.1%
-25200 1
< 0.1%
-22606.8 1
< 0.1%
-14156.4 1
< 0.1%
-13485.6 1
< 0.1%
-12684 1
< 0.1%
-12134.4 1
< 0.1%
-11680.8 1
< 0.1%
-11284.8 1
< 0.1%
ValueCountFrequency (%)
163211958 1
< 0.1%
32493420 1
< 0.1%
16800000 1
< 0.1%
14351192.4 1
< 0.1%
9619698 1
< 0.1%
9567460.8 1
< 0.1%
8421901.2 1
< 0.1%
8220792 1
< 0.1%
7937396.4 1
< 0.1%
6519902.4 1
< 0.1%

highest_balance
Real number (ℝ)

Missing  Skewed 

Distinct5140
Distinct (%)65.6%
Missing409
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean219202.73
Minimum501
Maximum1.800005 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.6 KiB
2025-03-11T22:56:47.190935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum501
5-th percentile4824
Q123453
median44047
Q3100500
95-th percentile531500
Maximum1.800005 × 108
Range1.8 × 108
Interquartile range (IQR)77047

Descriptive statistics

Standard deviation2814536.4
Coefficient of variation (CV)12.839879
Kurtosis2599.7929
Mean219202.73
Median Absolute Deviation (MAD)27475
Skewness47.718634
Sum1.7187686 × 109
Variance7.9216152 × 1012
MonotonicityNot monotonic
2025-03-11T22:56:47.262694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100500 151
 
1.8%
150500 102
 
1.2%
200500 84
 
1.0%
30500 66
 
0.8%
250500 54
 
0.7%
300500 53
 
0.6%
500500 53
 
0.6%
50500 49
 
0.6%
400500 42
 
0.5%
40500 39
 
0.5%
Other values (5130) 7148
86.6%
(Missing) 409
 
5.0%
ValueCountFrequency (%)
501 4
< 0.1%
502 1
 
< 0.1%
511 1
 
< 0.1%
514 1
 
< 0.1%
518 1
 
< 0.1%
550 1
 
< 0.1%
556 1
 
< 0.1%
581 1
 
< 0.1%
600 1
 
< 0.1%
601 8
0.1%
ValueCountFrequency (%)
180000500 1
< 0.1%
100000500 1
< 0.1%
95464005 1
< 0.1%
85000500 1
< 0.1%
35661277 1
< 0.1%
18000500 1
< 0.1%
14000500 1
< 0.1%
12000500 1
< 0.1%
10000500 1
< 0.1%
8580500 1
< 0.1%

report_date
Date

Missing 

Distinct1862
Distinct (%)26.1%
Missing1114
Missing (%)13.5%
Memory size64.6 KiB
Minimum1996-02-24 00:00:00
Maximum2016-06-17 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-11T22:56:47.413772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:47.486395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2025-03-11T22:56:44.990011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.563850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.178755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.836858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.409917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.982341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.549941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.206185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.753715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.312931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.051644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.643171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.239515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.897124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.470114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.042683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.610816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.263238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.813621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.375916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.111289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.702545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.295125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.953060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.525854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.098730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.746984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.318159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.869510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.436023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.169518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.762087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.351887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.009055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.582617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.155475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.803071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.372038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.926101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.495155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.228835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.821730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.408805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.066441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.639868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.211497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.860252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.425830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.982517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.635114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.287050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.879959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.466214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.122941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.696333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.266350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.917841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.478941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.038498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.692822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.346242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:39.939818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.524355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.179453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.753622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.322884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.974931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.534083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.094554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-03-11T22:56:45.402887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-03-11T22:56:42.376841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.029013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.584457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.150108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.810508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.456106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.055353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.633922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.289188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.863525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.432285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.085398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.640981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.204835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.865858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:45.517570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.117831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:40.705084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.351302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:41.922863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:42.491807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.146082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:43.697239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.260459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-11T22:56:44.927670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-11T22:56:47.541921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
OVD_sumOVD_t1OVD_t2OVD_t3highest_balanceidnew_balancepay_normalprod_codeprod_limit
OVD_sum1.0000.8940.6350.5590.015-0.034-0.1190.0770.042-0.095
OVD_t10.8941.0000.5420.3010.021-0.021-0.0800.1250.035-0.061
OVD_t20.6350.5421.0000.5250.008-0.005-0.1350.0160.024-0.139
OVD_t30.5590.3010.5251.000-0.007-0.027-0.138-0.0680.020-0.142
highest_balance0.0150.0210.008-0.0071.000-0.0310.3510.186-0.3630.474
id-0.034-0.021-0.005-0.027-0.0311.0000.0150.0100.0250.026
new_balance-0.119-0.080-0.135-0.1380.3510.0151.0000.102-0.0970.327
pay_normal0.0770.1250.016-0.0680.1860.0100.1021.0000.1190.022
prod_code0.0420.0350.0240.020-0.3630.025-0.0970.1191.0000.036
prod_limit-0.095-0.061-0.139-0.1420.4740.0260.3270.0220.0361.000

Missing values

2025-03-11T22:56:45.605949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-11T22:56:45.671147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-03-11T22:56:45.746051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idOVD_t1OVD_t2OVD_t3OVD_sumpay_normalprod_codeprod_limitupdate_datenew_balancehighest_balancereport_date
058987402000011016500.004/12/20160.0NaNNaN
158995151000015NaN04/12/2016588720.0491100.0NaN
258997200000025NaN04/12/2016840000.0700500.022/04/2016
354988608000031037400.003/12/20168425.27520.025/04/2016
4549877630000210NaN03/12/201615147.6NaN26/04/2016
559004828000031088000.002/12/20163196.86193.015/04/2016
658994429000021016500.002/12/20163252.03210.0NaN
754987756000021NaN02/12/2016365331.6304943.0NaN
858988028000040NaN02/12/201616795.228500.019/04/2016
958993180000036NaN02/12/201626688.031300.020/03/2016
idOVD_t1OVD_t2OVD_t3OVD_sumpay_normalprod_codeprod_limitupdate_datenew_balancehighest_balancereport_date
824059003535000046NaNNaN8332.811040.0NaN
8241549882440000213NaNNaN46041.645499.0NaN
824258998715000012NaNNaN154012.8128844.016/12/2015
824358998715000012NaNNaN1448944.82415400.022/11/2015
82445899914500001412NaNNaN0.0126500.0NaN
8245589954780000915NaNNaN0.0NaNNaN
824654992408000012NaNNaN0.0NaNNaN
8247549882090000513NaNNaN20654.433315.0NaN
824854992408000012NaNNaN0.0NaNNaN
824954989207000015NaNNaN240000.0200500.0NaN

Duplicate rows

Most frequently occurring

idOVD_t1OVD_t2OVD_t3OVD_sumpay_normalprod_codeprod_limitupdate_datenew_balancehighest_balancereport_date# duplicates
2954992408000012NaNNaN0.0NaNNaN4
3058982978000010NaN07/11/20110.0NaNNaN3
49589896000000415NaN26/04/20150.0100500.026/04/20153
505898960000002010125400.028/03/2014100155.6121376.025/11/20153
515898960000003610NaN12/08/201237899.659730.023/10/20153
0549854101006410NaN08/11/20070.011676.026/02/20082
1549869480000110NaN16/08/19970.0NaNNaN2
2549873360065196210NaN15/01/20020.091755.014/03/20142
354988645000026NaN10/05/20110.014500.022/06/20122
4549892510000010NaN19/04/19970.0NaNNaN2